---
license: agpl-3.0
tags:
- soccer
- video
- spotting
- localization
---
# ⚽ OpenSportsLib Localization Model (E2E)

## 📌 Overview

This model is a **video-based localization model** built using the **OpenSportsLib**, designed for **soccer action localization**.

- **Task**: Action Spotting / Localization  
- **Architecture**: E2E 
- **Backend**: Dali
- **Library**: OpenSportsLib  
- **Input**: Video clips  (224p)

---

## 📂 Dataset

### Training Dataset

This model is trained on the **SoccerNet – Ball Action Spotting 2023 (2 classes)**:

👉 https://huggingface.co/datasets/OpenSportsLab/soccernetpro-localization-snbas/tree/224p-2023

- **Domain**: Soccer video understanding  
- **Task**: Action Spotting  
- **Modality**: Video
- **Classes**: [PASS, DRIVE]

---

## 📊 Benchmark Results

| Metric       | Score |
|--------------|------|
| tight mAP      | 71.48 |
| loose mAP     | 85.62 |

---

## 🔧 Using with OpenSportsLib

For more details about OpenSportsLib visit the below link

👉 Github - https://github.com/OpenSportsLab/opensportslib

👉 PyPi - https://pypi.org/project/opensportslib/

👉 Documentations - https://opensportslab.github.io/opensportslib/


### Import the library

```python
import opensportslib
print("OpenSportsLib imported successfully")
```

### Run inference

```python
from opensportslib.apis import LocalizationModel

my_model = LocalizationModel(
    config="/path/to/localization.yaml",
👉   weights="OpenSportsLab/OSL-loc-snbas-2023-e2e",
)

predictions = my_model.infer(
    test_set="/path/to/test.json",
)

saved_predictions = my_model.save_predictions(
    output_path="/path/to/predictions.json",
    predictions=predictions,
)

metrics = my_model.evaluate(
    test_set="/path/to/test.json",
    predictions=saved_predictions,
)

print(metrics)
```
---

## 📜 License

- **Open source license**: AGPL 3.0 for research, academic, and community use.

- **Commercial license**: For proprietary or commercial deployment, please contact the project maintainers.

__

## 📎 Citation
```
@misc{opensportslib_e2e_localization_snbas_2023,
  title={OpenSportsLib Localization E2E SNBAS 2023},
  author={OpenSportsLab},
  year={2026},
  howpublished={https://huggingface.co/OpenSportsLab/oslib-e2e-localization-snbas-2023}
}
```

---

## 🙏 Acknowledgements

- **Dataset**: SoccerNet / OpenSportsLab  
- **Library**: https://github.com/OpenSportsLab/opensportslib